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How to deal with this when I use numpy.array() to deal with 'list'？

import cv2
import numpy

list_pixel=
list_label=
for i in range(0,10):
for j in range(0,10):
list_pixel.append(cv2.imread("C:\Users\kimcho\Desktop\testdata\testdata_"+str(i)+"_0"+str(j)+".png",0))
list_label.append(i)
j=0
list_pixel.pop(0)
list_label.pop(0)
list_pixel=numpy.array(list_pixel)
print(list_pixel)
print(list_pixel.shape)
print(list_pixel[0].shape)


How to deal with this when I use numpy.array() to deal with 'list'？I wanna make datasets by imitating keras.But,the datasets I made didn't satisfy me.I want it to act like keras,to return a value like this:

It can return a value of(60000,28,28)

But as for my datasets,it can only return like this:

Only return a value of(99,)—— I got 99 pictures and I want to load their pixel into list_pixel

Here is my code:

Hoping anyone can help me solve this problem.Deeply thank you!!!

1 Answer
1

When using cv2.imread you already load the image as a numpy array.

cv2.imread

A simple approach to it is the following:

import cv2
import numpy as np

list_label = np.arange(0, 10)
path = "C:\Users\kimcho\Desktop\testdata\testdata_{0}_0{1}.png"
list_pixel = np.array([
cv2.imread(path.format(i, j), 0) for i in range(0, 10)
for j in range(0, 10)
])


Let's try it on a simple scenario: we suppose there is just an image 28x28 in size, such as this one:

Let's say it is in the path my/path/image.png.

my/path/image.png

import cv2
import numpy as np

list_label = np.arange(0, 10)
path = "my/path/image.png"
list_pixel = np.array([
cv2.imread(path,0) for i in range(0, 10)
for j in range(0, 10)
])


When running list_pixel.shape you get (100, 28, 28).

list_pixel.shape

(100, 28, 28)

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